import sys

from ..src.database import database

if __name__ == "__main__":
    #db = database(db_path = './database', embedding_model = './embedding_models/AI-ModelScope/nomic-embed-text-v1/')
    #text = "hahaha"
    #print(db.get_embeddings([text]))

    from sentence_transformers import SentenceTransformer

    model = SentenceTransformer("./embedding_models/AI-ModelScope/nomic-embed-text-v1", trust_remote_code=True)
    sentences = ['search_document: TSNE is a dimensionality reduction algorithm created by Laurens van Der Maaten']
    embeddings = model.encode(sentences)
    print(embeddings)
